On the public citation graph

A Comparative Study of Using Deep Learning Algorithms in Network Intrusion Detection

https://doi.org/10.1109/access.2024.3389096
0 signed · 120 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ett.4150openalex-snapshot
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
inferredcites →https://doi.org/10.1007/978-3-030-23502-4_12openalex-snapshot
Dynamic Network Anomaly Detection System by Using Deep Learning Techniques
inferredcites →https://doi.org/10.1007/978-3-540-30143-1_11openalex-snapshot
Anomalous Payload-Based Network Intrusion Detection
inferredcites →https://doi.org/10.1007/978-3-642-20505-7_26openalex-snapshot
Hybrid Intelligent Intrusion Detection Scheme
inferredcites →https://doi.org/10.1007/s11235-018-0475-8openalex-snapshot
A comprehensive survey on network anomaly detection
inferredcites →https://doi.org/10.1016/j.asoc.2022.108768openalex-snapshot
A two-stage intrusion detection system with auto-encoder and LSTMs
inferredcites →https://doi.org/10.1016/j.comnet.2007.02.001openalex-snapshot
An overview of anomaly detection techniques: Existing solutions and latest technological trends
inferredcites →https://doi.org/10.1016/j.cose.2022.102675openalex-snapshot
A systematic literature review of methods and datasets for anomaly-based network intrusion detection
inferredcites →https://doi.org/10.1016/j.eswa.2014.11.009openalex-snapshot
A novel feature-selection approach based on the cuttlefish optimization algorithm for intrusion detection systems
inferredcites →https://doi.org/10.1016/j.neucom.2019.11.016openalex-snapshot
A novel statistical analysis and autoencoder driven intelligent intrusion detection approach
inferredcites →https://doi.org/10.1049/cit2.12078openalex-snapshot
Network anomaly detection using deep learning techniques
inferredcites →https://doi.org/10.1109/access.2020.2973023openalex-snapshot
An Unsupervised Deep Learning Model for Early Network Traffic Anomaly Detection
inferredcites →https://doi.org/10.1109/access.2021.3116612openalex-snapshot
Improving Performance of Autoencoder-Based Network Anomaly Detection on NSL-KDD Dataset
inferredcites →https://doi.org/10.1109/access.2021.3126834openalex-snapshot
Machine Learning in Network Anomaly Detection: A Survey
inferredcites →https://doi.org/10.1109/access.2023.3263155openalex-snapshot
Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection
inferredcites →https://doi.org/10.1109/cbd.2014.41openalex-snapshot
An Intrusion Detection Model Based on Deep Belief Networks
inferredcites →https://doi.org/10.1109/cisda.2009.5356528openalex-snapshot
A detailed analysis of the KDD CUP 99 data set
inferredcites →https://doi.org/10.1109/csac.2003.1254306openalex-snapshot
Bayesian event classification for intrusion detection
inferredcites →https://doi.org/10.1109/ibigdelft.2018.8625318openalex-snapshot
Intrusion Detection System with Recursive Feature Elimination by Using Random Forest and Deep Learning Classifier
inferredcites →https://doi.org/10.1109/icc40277.2020.9148946openalex-snapshot
PacketCGAN: Exploratory Study of Class Imbalance for Encrypted Traffic Classification Using CGAN
inferredcites →https://doi.org/10.1109/iccisci.2019.8716389openalex-snapshot
Developing a Network Attack Detection System Using Deep Learning
inferredcites →https://doi.org/10.1109/mc.2020.3004171openalex-snapshot
Deep Learning
inferredcites →https://doi.org/10.1109/ssci.2017.8280825openalex-snapshot
Intrusion detection of multiple attack classes using a deep neural net ensemble
inferredcites →https://doi.org/10.1109/tc.2016.2519914openalex-snapshot
Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm
inferredcites →https://doi.org/10.1109/tetci.2017.2772792openalex-snapshot
A Deep Learning Approach to Network Intrusion Detection
inferredcites →https://doi.org/10.1109/wincom.2016.7777224openalex-snapshot
Deep learning approach for Network Intrusion Detection in Software Defined Networking
inferredcites →https://doi.org/10.1111/coin.12220openalex-snapshot
Empirical study on multiclass classification‐based network intrusion detection
inferredcites →https://doi.org/10.1111/exsy.13066openalex-snapshot
Network intrusion detection system: A survey on artificial intelligence‐based techniques
inferredcites →https://doi.org/10.1145/382912.382923openalex-snapshot
Testing Intrusion detection systems
inferredcites →https://doi.org/10.1186/s13677-023-00574-9openalex-snapshot
A Transformer-based network intrusion detection approach for cloud security
inferredcites →https://doi.org/10.1186/s42400-019-0038-7openalex-snapshot
Survey of intrusion detection systems: techniques, datasets and challenges
inferredcites →https://doi.org/10.14257/ijsia.2015.9.5.21openalex-snapshot
A Hybrid Malicious Code Detection Method based on Deep Learning
inferredcites →https://doi.org/10.3233/apc220014openalex-snapshot
Network Anomaly Detection Using Hybrid Deep Learning Technique
inferredcites →https://doi.org/10.3390/app12094184openalex-snapshot
Network Intrusion Detection Model Based on CNN and GRU
inferredcites →https://doi.org/10.3390/app9163414openalex-snapshot
An LSTM-Based Deep Learning Approach for Classifying Malicious Traffic at the Packet Level
inferredcites →https://doi.org/10.3390/electronics11101531openalex-snapshot
A Novel Two-Stage Deep Learning Structure for Network Flow Anomaly Detection
inferredcites →https://doi.org/10.3390/electronics11142158openalex-snapshot
Machine Learning-Based Anomaly Detection Using K-Mean Array and Sequential Minimal Optimization
inferredcites →https://doi.org/10.3390/s21217070openalex-snapshot
Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
inferredcites →https://doi.org/10.3390/s22124405openalex-snapshot
DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic
inferredcites →https://doi.org/10.3390/s23042171openalex-snapshot
Network Anomaly Intrusion Detection Based on Deep Learning Approach
inferredcites →https://doi.org/10.4108/eai.3-12-2015.2262516openalex-snapshot
A Deep Learning Approach for Network Intrusion Detection System
inferredcites →https://doi.org/10.48550/arxiv.1908.10271openalex-snapshot
TEST: an End-to-End Network Traffic Examination and Identification Framework Based on Spatio-Temporal Features Extraction
inferredcites →https://doi.org/10.5121/csit.2022.121106openalex-snapshot
A Novel Approach to Network Intrusion Detection System using Deep Learning for SDN: Futuristic Approach

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.5241031openalex-extracted
Assessing the Role of Data Preprocessing in the Effectiveness of Machine Learning Algorithms for Intrusion Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-06662-6_30openalex-snapshot
Maximizing Detection Coverage in IDS Through Hybrid Deep Learning Architectures
inferred← citeshttps://doi.org/10.1007/978-3-032-11411-2_6openalex-snapshot
Recurrent Neural Networks for Intrusion Detection Systems in Industrial-Internet of Things
inferred← citeshttps://doi.org/10.1007/978-3-032-33957-7_13openalex-snapshot
SpreadSentinel: A Forward-Chaining Approach to Early and Adaptive DDoS Mitigation
inferred← citeshttps://doi.org/10.1007/s11276-025-04083-2openalex-snapshot
Cyberattack detection using a golden pelican search algorithm optimized three-tier deep learning approach
inferred← citeshttps://doi.org/10.1007/s11277-026-12204-zopenalex-snapshot
Residual RSSI Fingerprinting with Decision Ensembles for High-Accuracy Urban LoRaWAN Localization
inferred← citeshttps://doi.org/10.1007/s12243-026-01183-8openalex-snapshot
Bloom filter matrix encoding of flows for multi-model intrusion detection and attack intensity prediction
inferred← citeshttps://doi.org/10.1007/s43926-025-00156-yopenalex-snapshot
Enhancing cybersecurity in IoT systems: a hybrid deep learning approach for real-time attack detection
inferred← citeshttps://doi.org/10.1007/s44443-026-00688-5openalex-snapshot
QuCAD–IDS: cross–domain network intrusion detection via hierarchical contrastive autoencoding and queue-based adaptive distillation
inferred← citeshttps://doi.org/10.1016/j.aej.2025.07.027openalex-snapshot
PRISM-IIoT: A holistic approach for privacy preservation in industrial IoT using advanced cryptography and blockchain-enabled auditability framework
inferred← citeshttps://doi.org/10.1016/j.chemolab.2025.105558openalex-snapshot
Enhancing IoT anomaly detection with the Dwarf Mongoose-Chaos optimized deep belief framework
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2025.110626openalex-snapshot
Unveiling IoT ecosystem security: A review of intelligent IDS, trends, challenges, and future directions
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.126854openalex-snapshot
Improved network anomaly detection system using optimized autoencoder − LSTM
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131859openalex-snapshot
Meta-learning meets transformers: A novel approach to enterprise network intrusion detection
inferred← citeshttps://doi.org/10.1016/j.fraope.2025.100310openalex-snapshot
Performance analysis of recurrent neural networks for intrusion detection systems in Industrial-Internet of Things
inferred← citeshttps://doi.org/10.1016/j.iot.2025.101667openalex-snapshot
Smart systems: A review of theory, applications, and recent advances
inferred← citeshttps://doi.org/10.1016/j.rineng.2025.107103openalex-snapshot
A novel hybrid CNN-CBAM-GRU method for intrusion detection in modern networks
inferred← citeshttps://doi.org/10.1016/j.sasc.2025.200422openalex-snapshot
DG-IRFC: Intelligent design and implementation of network intrusion detection system (NIDS)
inferred← citeshttps://doi.org/10.1038/s41598-026-35879-7openalex-snapshot
Novel transformer-based model for NID in fog computing environment
inferred← citeshttps://doi.org/10.1038/s41598-026-37367-4openalex-snapshot
Energy-efficient intrusion detection with a protocol-aware transformer–spiking hybrid model
inferred← citeshttps://doi.org/10.1038/s41598-026-51074-0openalex-snapshot
RNN-based detection of IoT malware using diverse feature engineering methods
inferred← citeshttps://doi.org/10.1080/03772063.2026.2699928openalex-snapshot
A Quantum-Inspired Intrusion Detection System for Serverless Computing using QMV4ECX framework
inferred← citeshttps://doi.org/10.1109/access.2025.3585783openalex-snapshot
Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure
inferred← citeshttps://doi.org/10.1109/aiotc66747.2025.11198675openalex-snapshot
Dynamic Semi-Supervised Learning Fusing Vision Transformers and Temporal Attention for Network Traffic Anomaly Detection
inferred← citeshttps://doi.org/10.1109/aistemedu67077.2025.11403913openalex-snapshot
Cloud-Driven Intrusion Detection Enhancement Using RNN and CNN on Network Traffic
inferred← citeshttps://doi.org/10.1109/blackseacom65655.2025.11193960openalex-snapshot
Evaluating Large Language Models for Anomaly Detection with Cost-Efficient Sampling: A Generalized Framework
inferred← citeshttps://doi.org/10.1109/computingcon64838.2025.11377351openalex-snapshot
Intrusion Detection in IoT Networks Using Bidirectional LSTM with Attention Mechanism
inferred← citeshttps://doi.org/10.1109/cvaa66438.2025.11193214openalex-snapshot
TransICNN-IDS: Improved convolutional Neural Network with Transformer for intrusion detection system
inferred← citeshttps://doi.org/10.1109/etecom66111.2025.11319132openalex-snapshot
Explainable AI-Driven Chronic Kidney Disease Prediction System
inferred← citeshttps://doi.org/10.1109/gridedge61154.2025.10887470openalex-snapshot
LSTM-Xgboost Model for Cyberattack Detection in Grid-Connected Solar PV Inverter System
inferred← citeshttps://doi.org/10.1109/hswtech64936.2025.11278131openalex-snapshot
Zero-Day Intrusion Detection via Byte-Level Packet Modeling Using PacketBER
inferred← citeshttps://doi.org/10.1109/icaibd69640.2026.11637141openalex-snapshot
TransDepth-CAE-Dual: Tabular Data Anomaly Detection Based on Dual-Branch Collaboration and Consistency Constraints
inferred← citeshttps://doi.org/10.1109/icaidm66813.2025.11293384openalex-snapshot
Construction of Deep Learning-Based Intrusion Detection and Classification Model for Computer Networks
inferred← citeshttps://doi.org/10.1109/iccces62661.2026.11437093openalex-snapshot
Comparative Evaluation of Hybrid Deep Learning Approaches for Intrusion Detection in Iot Based Wireless Sensor Networks: Traditional vs. Advanced Techniques
inferred← citeshttps://doi.org/10.1109/icccs69761.2026.11613268openalex-snapshot
Internet User Behavior Anomaly Detection with Complementary Fusion and Dynamic Interaction
inferred← citeshttps://doi.org/10.1109/iccit64611.2024.11021837openalex-snapshot
SVDCNet: SVD-Driven Convolutional Neural Network for Advanced Multi-Label Network Intrusion Detection
inferred← citeshttps://doi.org/10.1109/iccnct68477.2026.11590341openalex-snapshot
A Robust AI-Powered Framework for Network Intrusion Detection System with Secure-IntrusionNet and Intelligent Attack Classification
inferred← citeshttps://doi.org/10.1109/icesc65114.2025.11212287openalex-snapshot
Adaptive Threat Detection in Cloud Infrastructure using Hybrid Deep Learning Algorithms
inferred← citeshttps://doi.org/10.1109/icetes68504.2026.11519023openalex-snapshot
Comparative Evaluation of DenseNet, ResNet, and GoogLeNet Architectures
inferred← citeshttps://doi.org/10.1109/icetsis68266.2026.11549394openalex-snapshot
Operationalizing Generative and Agentic AI Across Complex Logistics Networks: Architecture, Governance, and Trust Models
inferred← citeshttps://doi.org/10.1109/icitiit68860.2026.11499501openalex-snapshot
A Lightweight IoT-Based Framework for Real-Time Packet Analysis and Network Threat Detection
inferred← citeshttps://doi.org/10.1109/icmcsi67283.2026.11412807openalex-snapshot
An Intelligent Real-Time Intrusion Detection System Using Optimized Random Forest on NSL-KDD Dataset
inferred← citeshttps://doi.org/10.1109/icoei65986.2025.11013553openalex-snapshot
A Hybrid Deep Learning Approach to Network Traffic Anomaly Detection Enhanced by SHAP and LIME Interpretability
inferred← citeshttps://doi.org/10.1109/icscsa66339.2025.11170923openalex-snapshot
A Comprehensive Survey of Threat Detection and Mitigation in Layered IoT Security Frameworks
inferred← citeshttps://doi.org/10.1109/iicaiet67254.2025.11265502openalex-snapshot
AI-Driven Network Intrusion Detection Systems: A Survey of Techniques, Datasets and Deployment Challenges
inferred← citeshttps://doi.org/10.1109/iscon65210.2025.11341062openalex-snapshot
A Comparative Analysis of Deep Learning Algorithms in Network Intrusion Detection System
inferred← citeshttps://doi.org/10.1109/opcs63516.2024.10720441openalex-snapshot
The Comprehensive Deep Learning Models for Phishing Attack Detection
inferred← citeshttps://doi.org/10.1109/qpain69676.2026.11546166openalex-snapshot
AI-Based Intrusion Detection Method for Enhanced Cybersecurity in Modern Network Traffic
inferred← citeshttps://doi.org/10.1109/spicscon69221.2025.11504173openalex-snapshot
Enhancing Network Intrusion Detection System Using Optimized Deep Learning
inferred← citeshttps://doi.org/10.1109/sti69347.2025.11367527openalex-snapshot
A Hybrid Deep Ensemble Framework for Intelligent Intrusion Detection and Classification in Data Center Environments
inferred← citeshttps://doi.org/10.1109/tifs.2025.3621017openalex-snapshot
DTF-VPP: A Dynamic Intrusion Detection Method Combining Transformer and Feature Filtering for Virtual Power Plant Network Security
inferred← citeshttps://doi.org/10.1109/tvt.2026.3663771openalex-snapshot
LSTM-1DResNet: An Intrusion Detection Model for Connected and Autonomous Vehicles Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/wd67713.2025.11302576openalex-snapshot
Bloom Filter Traffic Encoding for Multi-Model Intrusion Detection and Attack Quantification
inferred← citeshttps://doi.org/10.1371/journal.pone.0333038openalex-snapshot
A deep reinforcement based echo state network for network intrusion classification
inferred← citeshttps://doi.org/10.14569/ijacsa.2025.0160343openalex-snapshot
A Deep Learning-Based Framework for Real-Time Detection of Cybersecurity Threats in IoT Environments
inferred← citeshttps://doi.org/10.1504/ijict.2025.146911openalex-snapshot
Enhancing cybersecurity: network intrusion detection with hybrid machine learning and deep learning approaches
inferred← citeshttps://doi.org/10.1615/telecomradeng.2026060331openalex-snapshot
EFFECTIVE AND INTELLIGENT HACDL FRAMEWORK FOR ROBUST IOT SECURITY TOWARD MULTI-CLASS ATTACK DETECTION USING CAPSULE NETWORKS
inferred← citeshttps://doi.org/10.20944/preprints202505.0420.v1openalex-snapshot
Comparative Study of Supervised Learning Algorithms for Intrusion Detection with a Focus on Logistic Regression
inferred← citeshttps://doi.org/10.2139/ssrn.5243737openalex-snapshot
A Systematic Review of Machine Learning Approaches for Intrusion Detection: Insights from Logistic Regression
inferred← citeshttps://doi.org/10.22541/au.174648246.66123061/v1openalex-snapshot
Cloud-Based Intrusion Detection Systems: Performance Comparison of Binary Logistic Regression and Other Machine Learning Algorithms
inferred← citeshttps://doi.org/10.23919/icact63878.2025.10936304openalex-snapshot
An Enhanced Intrusion Detection Model with FeedForward Neural Network Classifier
inferred← citeshttps://doi.org/10.31436/iiumej.v27i2.4240openalex-snapshot
Stability-Aware Evaluation of a CNN–LSTM–DQN Intrusion Detection System for Zero-Day and Drifted Network Traffic
inferred← citeshttps://doi.org/10.32604/cmc.2025.064777openalex-snapshot
A Comprehensive Survey of Contemporary Anomaly Detection Methods for Securing Smart IoT Systems
inferred← citeshttps://doi.org/10.3390/app14166967openalex-snapshot
Comparative Analysis of Deep Convolutional Neural Network—Bidirectional Long Short-Term Memory and Machine Learning Methods in Intrusion Detection Systems
inferred← citeshttps://doi.org/10.3390/app15168833openalex-snapshot
Provenance Graph-Based Deep Learning Framework for APT Detection in Edge Computing
inferred← citeshttps://doi.org/10.3390/app16052243openalex-snapshot
DF-TransVAE: A Deep Fusion Network for Binary Classification-Based Anomaly Detection in Internet User Behavior
inferred← citeshttps://doi.org/10.3390/computers14110450openalex-snapshot
Cross-Domain Adversarial Alignment for Network Anomaly Detection Through Behavioral Embedding Enrichment
inferred← citeshttps://doi.org/10.3390/electronics15132922openalex-snapshot
Network Intrusion Detection Based on Global-Local Temporal Feature Fusion Using Transformer and BiLSTM
inferred← citeshttps://doi.org/10.3390/s25144309openalex-snapshot
FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments
inferred← citeshttps://doi.org/10.3390/sym18060939openalex-snapshot
Causality-Aware and Explainable Self-Supervised Spatio-Temporal Graph Learning for Hardware Trojan Detection
inferred← citeshttps://doi.org/10.3390/sym18091438openalex-snapshot
A Systematic Multi-Paradigm Evaluation Framework for Network Intrusion Detection in Fog-IoT Environments: Deep Learning, Transformer, and Ensemble Methods Across Deployment Tiers
inferred← citeshttps://doi.org/10.4018/979-8-3373-5062-2.ch001openalex-snapshot
Advanced Behavioral Analysis for Intrusion Detection Using Deep Learning and Machine Learning Techniques
inferred← citeshttps://doi.org/10.48084/etasr.13267openalex-snapshot
Enhancing Network Intrusion Detection for TLS Traffic Using Deep Learning
inferred← citeshttps://doi.org/10.48084/etasr.18412openalex-snapshot
Enhancing Vulnerability Detection Precision through Ensemble Learning with Large Language Models
inferred← citeshttps://doi.org/10.7717/peerj-cs.3306openalex-snapshot
A recurrent neural network for network-based intrusion detection
inferred← citeshttps://doi.org/10.7717/peerj-cs.3502openalex-snapshot
AI and post-quantum cryptography powered cybersecurity approaches for IoT systems: a literature review
inferred← citeshttps://doi.org/10.7759/s44389-026-00170-3openalex-snapshot
A Lightweight Hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) and AdaBoost Framework for Edge-Based Internet of Things (IoT) Intrusion Detection
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.